Free guide · For asset owners and operators

AI and asset management
Are you getting left behind?

A short, plain-English guide for asset owners: what AI can really do for whole-life asset management, why it depends on trusted asset information, and how to take the next step.

  • Eight practical use cases, and the information each one needs
  • The five-level AI maturity ladder: see where you stand
  • A 10-point readiness checklist to use with your team
Cover of the guide AI and Asset Management: are you getting left behind?

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What's inside

What's changing
How AI is moving asset management from fixing failures to predicting them, and from annual averages to tested scenarios.
Why information quality comes first
The asset information model, a trusted asset register, and treating information as an asset, in line with the ISO 55000 series.
Digital twins: where AI meets real assets
The loop from the asset, through sensors, the register and AI, to better decisions and better work on the ground.
Eight practical use cases
From predictive maintenance and defect detection to scenario testing, energy and carbon, with the information each one needs.
The AI maturity ladder
Five levels, from no AI to AI-assisted decisions at scale, with what each looks like.
A 10-point readiness checklist
Ten questions to answer with your team, a simple score, and the next steps that fit.

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This guide is general guidance, not professional advice. Decisions about assets, safety and investment stay with your organisation and its competent people.